Embodiments of the invention relate to information extraction from natural-language text, in particular, for using semantic abstraction based on translating natural-language parses into a collection of actions, roles and complimentary concepts using dependency parse trees.
With the rapid growth of textual content, information extraction is becoming increasing important as it is crucial for obtaining useful information from text. One major challenge for information extraction is that the same semantics can be expressed in many different ways. In order to develop information extraction programs, all the linguistic variants must be taken into account. Expressive information extraction systems permit the building of complex information extraction programs to handle the linguistic variants. However, the development of such programs over the raw text can be extremely time consuming and tedious.